{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "85a43a83",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "569cf928",
   "metadata": {
    "code_folding": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[71, 59, 75],\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
       "       [[64, 43, 18],\n",
       "        [64, 26, 93],\n",
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       "\n",
       "       [[28, 93, 55],\n",
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       "        [88, 78, 71],\n",
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       "        [42,  5, 24],\n",
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       "        [25, 73, 62],\n",
       "        [58, 68,  3],\n",
       "        [95,  3, 61],\n",
       "        [43, 86, 16],\n",
       "        [38, 82, 53],\n",
       "        [65, 63, 93],\n",
       "        [23, 85, 14],\n",
       "        [83,  9,  1],\n",
       "        [98, 42, 98],\n",
       "        [18, 61, 12],\n",
       "        [65, 26, 30],\n",
       "        [40, 75, 78],\n",
       "        [11, 30, 55],\n",
       "        [43, 78, 56],\n",
       "        [95, 93, 21],\n",
       "        [57, 72,  3],\n",
       "        [ 6, 46, 30],\n",
       "        [94,  5, 27],\n",
       "        [69, 70,  2],\n",
       "        [47, 40, 99],\n",
       "        [83, 48, 24],\n",
       "        [68,  2, 56],\n",
       "        [99, 90, 42],\n",
       "        [75, 16,  6],\n",
       "        [47, 72, 22],\n",
       "        [45, 89, 85],\n",
       "        [66, 79, 93],\n",
       "        [45, 44, 35],\n",
       "        [17, 74, 84],\n",
       "        [76, 76, 49],\n",
       "        [80, 57,  6],\n",
       "        [14, 61, 36],\n",
       "        [48, 87, 66],\n",
       "        [54, 12, 67],\n",
       "        [ 5, 86, 64],\n",
       "        [67, 21, 57],\n",
       "        [67,  1, 56],\n",
       "        [47, 73, 89],\n",
       "        [93, 26,  7],\n",
       "        [19, 90, 43]]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 随机生成数据，6个班，50个同学，3门成绩\n",
    "arr = np.random.randint(0,100,size=(6,50,3))\n",
    "arr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fe140685",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(300, 3)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 数据合并，形成score\n",
    "score = np.concatenate(arr,axis=0)\n",
    "score.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "4d0f4b41",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "       [1],\n",
       "       [2]])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "array([[71, 59, 75,  2],\n",
       "       [67, 71, 65,  1],\n",
       "       [19, 66, 87,  2],\n",
       "       ...,\n",
       "       [47, 73, 89,  2],\n",
       "       [93, 26,  7,  1],\n",
       "       [19, 90, 43,  2]])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 生成性别数组sex，水平叠加数组sex和score得到data\n",
    "# 男=1，女=2\n",
    "sex = np.random.randint(1,3,size=(300,1))\n",
    "data=np.concatenate([score,sex],axis=1)\n",
    "display(sex,data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "10a54f65",
   "metadata": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "男生Python、数学、语文成绩最低分别为： 1 , 1 , 1\n",
      "男生Python、数学、语文成绩最高分别为： 71 , 76 , 45\n",
      "男生Python、数学、语文成绩平均分分别为： 51.0 , 36.25 , 31.0\n",
      "男生Python、数学、语文成绩中位数分别为： 64.0 , 60.0 , 56.0\n",
      "男生Python、数学、语文成绩标准差分别为： 29.84 , 27.46 , 27.85\n",
      "女生Python、数学、语文成绩最低分别为： 2 , 2 , 2\n",
      "女生Python、数学、语文成绩最高分别为： 75 , 87 , 31\n",
      "女生Python、数学、语文成绩平均分分别为： 51.75 , 43.5 , 15.75\n",
      "女生Python、数学、语文成绩中位数分别为： 43.0 , 48.0 , 49.0\n",
      "女生Python、数学、语文成绩标准差分别为： 28.68 , 30.07 , 29.04\n"
     ]
    }
   ],
   "source": [
    "# 分别计算男女生各科成绩统计指标：最小值、最大值、平均分、中位数、标准差\n",
    "male = data[data[:,3] == 1]\n",
    "female = data[data[:,3] == 2]\n",
    "print('男生Python、数学、语文成绩最低分别为：',male.min(axis=1)[0],',',male.min(axis=1)[1],',',male.min(axis=1)[2])\n",
    "print('男生Python、数学、语文成绩最高分别为：',male.max(axis=1)[0],',',male.max(axis=1)[1],',',male.max(axis=1)[2])\n",
    "print('男生Python、数学、语文成绩平均分分别为：',male.mean(axis=1)[0],',',male.mean(axis=1)[1],',',male.mean(axis=1)[2])\n",
    "print('男生Python、数学、语文成绩中位数分别为：',np.median(male[:,0]),',',np.median(male[:,1]),',',np.median(male[:,2]))\n",
    "print('男生Python、数学、语文成绩标准差分别为：',np.round(np.std(male[:,0]),2),',',np.round(np.std(male[:,1]),2),',',np.round(np.std(male[:,2]),2))\n",
    "print('女生Python、数学、语文成绩最低分别为：',female.min(axis=1)[0],',',female.min(axis=1)[1],',',female.min(axis=1)[2])\n",
    "print('女生Python、数学、语文成绩最高分别为：',female.max(axis=1)[0],',',female.max(axis=1)[1],',',female.max(axis=1)[2])\n",
    "print('女生Python、数学、语文成绩平均分分别为：',female.mean(axis=1)[0],',',female.mean(axis=1)[1],',',female.mean(axis=1)[2])\n",
    "print('女生Python、数学、语文成绩中位数分别为：',np.median(female[:,0]),',',np.median(female[:,1]),',',np.median(female[:,2]))\n",
    "print('女生Python、数学、语文成绩标准差分别为：',np.round(np.std(female[:,0]),2),',',np.round(np.std(female[:,1]),2),',',np.round(np.std(female[:,2]),2))"
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